Your mission
- Design and maintain scalable pipelines to ingest and organize large volumes of time-series camera and sensor data (RGB, IR, acoustic, depth, IMU, and other modalities).
- Own and improve datasets for object detection and classification tasks, ensuring statistical robustness, diversity, and representativeness.
- Build and operate active learning loops to select high-value samples, reduce annotation cost, and continuously improve model performance.
- Write robust preprocessing pipelines using Python, NumPy, Pandas, and augmentation libraries like Albumentations.
- Manage labeling workflows, including QA rules, label consistency checks, vendor coordination, and dataset versioning.
- Collaborate with ML Engineers to fine-tune, train, and evaluate object detection models and feed insights back into the data pipeline.
- Analyze model weaknesses, uncover blind spots, and drive dataset improvements through statistical diagnostics and drift/bias detection.
- Create internal tools to visualize, audit, and analyze dataset quality, diversity, long-tail performance, and failure modes.
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